pattern recognition
Pattern recognition has been developed to ease the way of reading an great amount of information as a form of decoding. In the beginning a concept of mathematical analysis was underlayed, but later it became also associated with the field of connectivist research.
For a better explanation follows a short description of the historical line leading to such devices as facerecognition or irisscan.

Military developments of space determination through photography and radar evoked the idea of further mechanical translation systems. Combining this with the research in the automation of mental functions the two fields of artificial intelligence and cognitive (movie) psychology were introduced.

1 Automation of sight: From Photography to Computer Vision, p.10
Manovich, Lev
First developments lead to the field of pattern recognition. 'Pattern recognition is concerned with automatically detecting and identifying predetermined patterns in the flow of information. A typical example is character recognition, ...Instead of listening to every transmission, an operator would be alert if computer picked up certain words in the conversation.'1

2 De Landa in Automation of sight: From Photography to Computer Vision, p.11
Manovich, Lev

3 Forum Wissenschaft, 2/2002,
Wehrheim, Jan
The next step was to bring this together with image processing, which following M.De Landa was routinely used to correct for distortions made by satellite's imaging sensors and by atmospheric effects, sharpen out-of-focus images, and so on. This simply developed because there was no hope to go through all these images for the National Photographic Interpretation Center (NPIC). 'The computers had to be thaught to compare new imaginery of a given scene with old imaginery, ignoring what had not changed and calling the interpreter's attention to what had.'2From this fields computervision (robot sight, irisscan, smart engines) evolved, so up to now we have achieved 'thinking cameras' and 'algorythmic surveillance.'3
Thus the perspectival image became problematic for 3D object recognition so today modern vision systems utilize a whole range of different range finders such as lasers or ultrasound.
Examples for the combining of diverse data transmission devices are GPS-systems and scanning devices. 'By systematically scanning the surface of an object, it directly produces a depth map, a record of an object's shape, which can be then matched to geometric models stored in computer memory thus bypassing the perspectival image altogether.' It is straight away put into code.
Here are some links to more and profound information:
A Forest of Sensors (research at MIT)
The Pattern Recognition Files
Imaging and Neuroscience by Heeger
Pattern Recognition by Toussaint